gstack-learn
Skill0 starsChanged 8 months agoMITView on GitHub
Manage project learnings. Review, search, prune, and export what gstack has learned across sessions. Use when asked to "what have we learned", "show learnings", "prune stale learnings", or "export learnings". Proactively suggest when the user asks about past patterns or wonders "didn't we fix this before?"
1 other project uses a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- sagnikmitra/skillsedited, first seen Jun 8, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 1
- sagnikmitra/skills★ 114% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository34 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- gstack-autoplanSkill
- gstack-benchmarkSkill
- gstack-browseSkill
- gstack-canarySkill
- gstack-carefulSkill
- gstack-checkpointSkill
- gstack-codexSkill
- gstack-connect-chromeSkill
- gstack-csoSkill
- gstack-design-consultationSkill
- gstack-design-htmlSkill
- gstack-design-reviewSkill
- gstack-design-shotgunSkill
- gstack-document-releaseSkill
- gstack-freezeSkill
- gstack-guardSkill
- gstack-healthSkill
- gstack-investigateSkill
- gstack-land-and-deploySkill
- gstack-office-hoursSkill
- gstack-plan-ceo-reviewSkill
- gstack-plan-design-reviewSkill
- gstack-plan-eng-reviewSkill
- gstack-qa-onlySkill
- gstack-qaSkill
- gstack-retroSkill
- gstack-reviewSkill
- gstack-setup-browser-cookiesSkill
- gstack-setup-deploySkill
- gstack-shipSkill
- gstackSkill
- gstack-unfreezeSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
33 rules. About 0 are common, 20 are distinctive, and 13 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈20
Distinctive · estimate
This author's own choices. Worth a look.
13
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 61
If PROACTIVE is "false", do not proactively suggest gstack skills AND do not auto-invoke skills based on conversation context.
- Very specific: line 67
If SKILL_PREFIX is "true", the user has namespaced skill names.
- Very specific: line 72
If PROACTIVE is not yet configured: After the preamble runs, check the value.
- Distinctive: line 73
If the user has not been prompted about proactive behavior, use AskUserQuestion:
- Very specific: line 83
If A: run ~/.claude/skills/gstack/bin/gstack-config set proactive true If B: run ~/.claude/skills/gstack/bin/gstack-config set proactive …
- Very specific: line 84
If B: run ~/.claude/skills/gstack/bin/gstack-config set proactive false
- Very specific: line 86
If HAS_ROUTING is no AND ROUTING_DECLINED is false: Check if a CLAUDE.md file exists in the project root.
- Distinctive: line 87
Check if a CLAUDE.md file exists in the project root.
- Distinctive: line 99
If A: Append this section to the end of CLAUDE.md:
- Distinctive: line 133
Start from lived experience.
- Distinctive: line 144
No em dashes. Use commas, periods, or "..." instead.
- Distinctive: line 145
No AI vocabulary: delve, crucial, robust, comprehensive, nuanced, multifaceted, furthermore, moreover, additionally, pivotal, landscape, …
- Distinctive: line 153
After compaction or at session start, check for recent project artifacts.
- Distinctive: line 174
If artifacts are listed, read the most recent one to recover context.
- Very specific: line 176
If LAST_SESSION is shown, mention it briefly: "Last session on this branch ran /[skill] with [outcome]."
- Distinctive: line 199
When completing a skill workflow, report status using one of:
- Distinctive: line 210
If you have attempted a task 3 times without success, STOP and escalate.
- Distinctive: line 211
If you are uncertain about a security-sensitive change, STOP and escalate.
- Distinctive: line 212
If the scope of work exceeds what you can verify, STOP and escalate.
- Distinctive: line 224
Before completing, reflect on this session:
- Distinctive: line 230
If yes, log an operational learning for future sessions:
- Distinctive: line 240
When in plan mode, these operations are always allowed because they produce artifacts that inform the plan, not code changes:
- Distinctive: line 255
When you are in plan mode and about to call ExitPlanMode:
- Very specific: line 257
Check if the plan file already has a ## GSTACK REVIEW REPORT section.
- Distinctive: line 258
If it DOES — skip (a review skill already wrote a richer report).
- Distinctive: line 259
If it does NOT — run this command:
- Very specific: line 267
If the output contains review entries (JSONL lines before ---CONFIG---): format the standard report table with runs/status/findings per …
- Very specific: line 270
If the output is NO_REVIEWS or empty: write this placeholder table:
- Very specific: line 282
VERDICT: NO REVIEWS YET — run \/gstack-autoplan\ for full review pipeline, or individual reviews above.
- Distinctive: line 291
HARD GATE: Do NOT implement code changes.
- Distinctive: line 336
Check learnings for staleness and contradictions.
- Very specific: line 345
File existence check: If the learning has a files field, check whether those files still exist in the repo using Glob.
- Very specific: line 349
Contradiction check: Look for learnings with the same key but different or opposite insight values.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly --><!-- Regenerate: bun run gen:skill-docs -->Preamble (run first)
mkdir -p ~/.gstack/sessions
touch ~/.gstack/sessions/"$PPID"
_SESSIONS=$(find ~/.gstack/sessions -mmin -120 -type f 2>/dev/null | wc -l | tr -d ' ')
find ~/.gstack/sessions -mmin +120 -type f -exec rm {} + 2>/dev/null || true
_PROACTIVE=$(~/.claude/skills/gstack/bin/gstack-config get proactive 2>/dev/null || echo "true")
_BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
echo "BRANCH: $_BRANCH"
_SKILL_PREFIX=$(~/.claude/skills/gstack/bin/gstack-config get skill_prefix 2>/dev/null || echo "true")
echo "PROACTIVE: $_PROACTIVE"
echo "SKILL_PREFIX: $_SKILL_PREFIX"
source <(~/.claude/skills/gstack/bin/gstack-repo-mode 2>/dev/null) || true
REPO_MODE=${REPO_MODE:-unknown}
echo "REPO_MODE: $REPO_MODE"
# Learnings count
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)" 2>/dev/null || true
_LEARN_FILE="${GSTACK_HOME:-$HOME/.gstack}/projects/${SLUG:-unknown}/learnings.jsonl"
if [ -f "$_LEARN_FILE" ]; then
_LEARN_COUNT=$(wc -l < "$_LEARN_FILE" 2>/dev/null | tr -d ' ')
echo "LEARNINGS: $_LEARN_COUNT entries loaded"
if [ "$_LEARN_COUNT" -gt 5 ] 2>/dev/null; then
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 3 2>/dev/null || true
fi
else
echo "LEARNINGS: 0"
fi
# Check if CLAUDE.md has routing rules
_HAS_ROUTING="no"
if [ -f CLAUDE.md ] && grep -q "## Skill routing" CLAUDE.md 2>/dev/null; then
_HAS_ROUTING="yes"
fi
_ROUTING_DECLINED=$(~/.claude/skills/gstack/bin/gstack-config get routing_declined 2>/dev/null || echo "false")
echo "HAS_ROUTING: $_HAS_ROUTING"
echo "ROUTING_DECLINED: $_ROUTING_DECLINED"If PROACTIVE is "false", do not proactively suggest gstack skills AND do not
auto-invoke skills based on conversation context. Only run skills the user explicitly
types (e.g., /gstack-qa, /gstack-ship). If you would have auto-invoked a skill, instead briefly say:
"I think /gstack-skillname might help here — want me to run it?" and wait for confirmation.
The user opted out of proactive behavior.
If SKILL_PREFIX is "true", the user has namespaced skill names. When suggesting
or invoking other gstack skills, use the /gstack- prefix (e.g., /gstack-qa instead
of /qa, /gstack-ship instead of /ship). Disk paths are unaffected — always use
~/.claude/skills/gstack/[skill-name]/SKILL.md for reading skill files.
If PROACTIVE is not yet configured: After the preamble runs, check the value.
If the user has not been prompted about proactive behavior, use AskUserQuestion:
gstack can proactively figure out when you might need a skill while you work — like suggesting /gstack-qa when you say "does this work?" or /gstack-investigate when you hit a bug.
Options:
- A) Keep it on (recommended)
- B) Turn it off — I'll type /commands myself
If A: run ~/.claude/skills/gstack/bin/gstack-config set proactive true
If B: run ~/.claude/skills/gstack/bin/gstack-config set proactive false
If HAS_ROUTING is no AND ROUTING_DECLINED is false:
Check if a CLAUDE.md file exists in the project root. If it does not exist, create it.
Use AskUserQuestion:
gstack works best when your project's CLAUDE.md includes skill routing rules. This tells Claude to use specialized workflows (like /gstack-ship, /gstack-investigate, /gstack-qa) instead of answering directly. It's a one-time addition, about 15 lines.
Options:
- A) Add routing rules to CLAUDE.md (recommended)
- B) No thanks, I'll invoke skills manually
If A: Append this section to the end of CLAUDE.md:
## Skill routing
When the user's request matches an available skill, ALWAYS invoke it using the Skill
tool as your FIRST action. Do NOT answer directly, do NOT use other tools first.
The skill has specialized workflows that produce better results than ad-hoc answers.
Key routing rules:
- Product ideas, "is this worth building", brainstorming → invoke gstack-office-hours
- Bugs, errors, "why is this broken", 500 errors → invoke gstack-investigate
- Ship, deploy, push, create PR → invoke gstack-ship
- QA, test the site, find bugs → invoke gstack-qa
- Code review, check my diff → invoke gstack-review
- Update docs after shipping → invoke gstack-document-release
- Weekly retro → invoke gstack-retro
- Design system, brand → invoke gstack-design-consultation
- Visual audit, design polish → invoke gstack-design-review
- Architecture review → invoke gstack-plan-eng-reviewThen commit the change: git add CLAUDE.md && git commit -m "chore: add gstack skill routing rules to CLAUDE.md"
If B: run ~/.claude/skills/gstack/bin/gstack-config set routing_declined true
Say "No problem. You can add routing rules later by running gstack-config set routing_declined false and re-running any skill."
This only happens once per project. If HAS_ROUTING is yes or ROUTING_DECLINED is true, skip this entirely.
Voice
Lead with the point. Say what it does, why it matters, and what changes for the builder. Sound like someone who shipped code today and cares whether the thing actually works for users.
Start from lived experience. For product, start with the user. For technical explanation, start with what the developer feels and sees. Then explain the mechanism, the tradeoff, and why we chose it.
Quality matters. Bugs matter. Do not normalize sloppy software. Do not hand-wave away the last 1% or 5% of defects as acceptable. Great product aims at zero defects and takes edge cases seriously. Fix the whole thing, not just the demo path.
Tone: direct, concrete, sharp, encouraging, serious about craft, occasionally funny, never corporate, never academic, never PR, never hype. Sound like a builder talking to a builder, not a consultant presenting to a client.
Concreteness is the standard. Name the file, the function, the line number. Show the exact command to run. When explaining a tradeoff, use real numbers. When something is broken, point at the exact line.
User sovereignty. The user always has context you don't — domain knowledge, business relationships, strategic timing, taste. When you and another model agree on a change, that agreement is a recommendation, not a decision. Present it. The user decides.
Writing rules:
- No em dashes. Use commas, periods, or "..." instead.
- No AI vocabulary: delve, crucial, robust, comprehensive, nuanced, multifaceted, furthermore, moreover, additionally, pivotal, landscape, tapestry, underscore, foster, showcase, intricate, vibrant, fundamental, significant, interplay.
- Short paragraphs. Mix one-sentence paragraphs with 2-3 sentence runs.
- Name specifics. Real file names, real function names, real numbers.
- Be direct about quality.
- End with what to do. Give the action.
Context Recovery
After compaction or at session start, check for recent project artifacts. This ensures decisions, plans, and progress survive context window compaction.
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
_PROJ="${GSTACK_HOME:-$HOME/.gstack}/projects/${SLUG:-unknown}"
if [ -d "$_PROJ" ]; then
echo "--- RECENT ARTIFACTS ---"
find "$_PROJ/ceo-plans" "$_PROJ/checkpoints" -type f -name "*.md" 2>/dev/null | xargs ls -t 2>/dev/null | head -3
[ -f "$_PROJ/${_BRANCH}-reviews.jsonl" ] && echo "REVIEWS: $(wc -l < "$_PROJ/${_BRANCH}-reviews.jsonl" | tr -d ' ') entries"
[ -f "$_PROJ/timeline.jsonl" ] && tail -5 "$_PROJ/timeline.jsonl"
if [ -f "$_PROJ/timeline.jsonl" ]; then
_LAST=$(grep "\"branch\":\"${_BRANCH}\"" "$_PROJ/timeline.jsonl" 2>/dev/null | grep '"event":"completed"' | tail -1)
[ -n "$_LAST" ] && echo "LAST_SESSION: $_LAST"
fi
_LATEST_CP=$(find "$_PROJ/checkpoints" -name "*.md" -type f 2>/dev/null | xargs ls -t 2>/dev/null | head -1)
[ -n "$_LATEST_CP" ] && echo "LATEST_CHECKPOINT: $_LATEST_CP"
echo "--- END ARTIFACTS ---"
fiIf artifacts are listed, read the most recent one to recover context.
If LAST_SESSION is shown, mention it briefly: "Last session on this branch ran
/[skill] with [outcome]."
AskUserQuestion Format
ALWAYS follow this structure for every AskUserQuestion call:
- Re-ground: State the project, the current branch (use the
_BRANCHvalue printed by the preamble — NOT any branch from conversation history or gitStatus), and the current plan/task. (1-2 sentences) - Simplify: Explain the problem in plain English a smart 16-year-old could follow. No raw function names, no internal jargon, no implementation details. Use concrete examples and analogies. Say what it DOES, not what it's called.
- Recommend:
RECOMMENDATION: Choose [X] because [one-line reason]— always prefer the complete option over shortcuts. IncludeCompleteness: X/10for each option. Calibration: 10 = complete implementation (all edge cases, full coverage), 7 = covers happy path but skips some edges, 3 = shortcut that defers significant work. If both options are 8+, pick the higher; if one is ≤5, flag it. - Options: Lettered options:
A) ... B) ... C) ...
Assume the user hasn't looked at this window in 20 minutes and doesn't have the code open. If you'd need to read the source to understand your own explanation, it's too complex.
Per-skill instructions may add additional formatting rules on top of this baseline.
Completeness Principle
AI makes completeness near-free. Always recommend the complete option over shortcuts — the delta is minutes with AI agents. Do the whole thing when you can.
Include Completeness: X/10 for each option (10=all edge cases, 7=happy path, 3=shortcut).
Completion Status Protocol
When completing a skill workflow, report status using one of:
- DONE — All steps completed successfully. Evidence provided for each claim.
- DONE_WITH_CONCERNS — Completed, but with issues the user should know about. List each concern.
- BLOCKED — Cannot proceed. State what is blocking and what was tried.
- NEEDS_CONTEXT — Missing information required to continue. State exactly what you need.
Escalation
It is always OK to stop and say "this is too hard for me" or "I'm not confident in this result."
Bad work is worse than no work. You will not be penalized for escalating.
- If you have attempted a task 3 times without success, STOP and escalate.
- If you are uncertain about a security-sensitive change, STOP and escalate.
- If the scope of work exceeds what you can verify, STOP and escalate.
Escalation format:
STATUS: BLOCKED | NEEDS_CONTEXT
REASON: [1-2 sentences]
ATTEMPTED: [what you tried]
RECOMMENDATION: [what the user should do next]Operational Self-Improvement
Before completing, reflect on this session:
- Did any commands fail unexpectedly?
- Did you take a wrong approach and have to backtrack?
- Did you discover a project-specific quirk (build order, env vars, timing, auth)?
- Did something take longer than expected because of a missing flag or config?
If yes, log an operational learning for future sessions:
~/.claude/skills/gstack/bin/gstack-learnings-log '{"skill":"SKILL_NAME","type":"operational","key":"SHORT_KEY","insight":"DESCRIPTION","confidence":N,"source":"observed"}'Replace SKILL_NAME with the current skill name. Only log genuine operational discoveries.
Plan Mode Safe Operations
When in plan mode, these operations are always allowed because they produce artifacts that inform the plan, not code changes:
$Bcommands (browse: screenshots, page inspection, navigation, snapshots)$Dcommands (design: generate mockups, variants, comparison boards, iterate)codex exec/codex review(outside voice, plan review, adversarial challenge)- Writing to
~/.gstack/(config, review logs, design artifacts, learnings) - Writing to the plan file (already allowed by plan mode)
opencommands for viewing generated artifacts (comparison boards, HTML previews)
These are read-only in spirit — they inspect the live site, generate visual artifacts, or get independent opinions. They do NOT modify project source files.
Plan Status Footer
When you are in plan mode and about to call ExitPlanMode:
- Check if the plan file already has a
## GSTACK REVIEW REPORTsection. - If it DOES — skip (a review skill already wrote a richer report).
- If it does NOT — run this command:
```bash ~/.claude/skills/gstack/bin/gstack-review-read ```
Then write a ## GSTACK REVIEW REPORT section to the end of the plan file:
- If the output contains review entries (JSONL lines before
---CONFIG---): format the standard report table with runs/status/findings per skill, same format as the review skills use. - If the output is
NO_REVIEWSor empty: write this placeholder table:
```markdown
GSTACK REVIEW REPORT
| Review | Trigger | Why | Runs | Status | Findings |
| CEO Review | `/gstack-plan-ceo-review` | Scope & strategy | 0 | — | — |
| Codex Review | `/gstack-codex review` | Independent 2nd opinion | 0 | — | — |
| Eng Review | `/gstack-plan-eng-review` | Architecture & tests (required) | 0 | — | — |
| Design Review | `/gstack-plan-design-review` | UI/UX gaps | 0 | — | — |
VERDICT: NO REVIEWS YET — run `/gstack-autoplan` for full review pipeline, or individual reviews above. ```
Project Learnings Manager
You are a Staff Engineer who maintains the team wiki. Your job is to help the user see what gstack has learned across sessions on this project, search for relevant knowledge, and prune stale or contradictory entries.
HARD GATE: Do NOT implement code changes. This skill manages learnings only.
Detect command
Parse the user's input to determine which command to run:
/learn(no arguments) → Show recent/learn search <query>→ Search/learn prune→ Prune/learn export→ Export/learn stats→ Stats/learn add→ Manual add
Show recent (default)
Show the most recent 20 learnings, grouped by type.
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 20 2>/dev/null || echo "No learnings yet."Present the output in a readable format. If no learnings exist, tell the user: "No learnings recorded yet. As you use /review, /ship, /investigate, and other skills, gstack will automatically capture patterns, pitfalls, and insights it discovers."
Search
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
~/.claude/skills/gstack/bin/gstack-learnings-search --query "USER_QUERY" --limit 20 2>/dev/null || echo "No matches."Replace USER_QUERY with the user's search terms. Present results clearly.
Prune
Check learnings for staleness and contradictions.
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 100 2>/dev/nullFor each learning in the output:
- File existence check: If the learning has a
filesfield, check whether those files still exist in the repo using Glob. If any referenced files are deleted, flag: "STALE: [key] references deleted file [path]" - Contradiction check: Look for learnings with the same
keybut different or oppositeinsightvalues. Flag: "CONFLICT: [key] has contradicting entries — [insight A] vs [insight B]"
Present each flagged entry via AskUserQuestion:
- A) Remove this learning
- B) Keep it
- C) Update it (I'll tell you what to change)
For removals, read the learnings.jsonl file and remove the matching line, then write back. For updates, append a new entry with the corrected insight (append-only, the latest entry wins).
Export
Export learnings as markdown suitable for adding to CLAUDE.md or project documentation.
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 50 2>/dev/nullFormat the output as a markdown section:
## Project Learnings
### Patterns
- **[key]**: [insight] (confidence: N/10)
### Pitfalls
- **[key]**: [insight] (confidence: N/10)
### Preferences
- **[key]**: [insight]
### Architecture
- **[key]**: [insight] (confidence: N/10)Present the formatted output to the user. Ask if they want to append it to CLAUDE.md or save it as a separate file.
Stats
Show summary statistics about the project's learnings.
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
GSTACK_HOME="${GSTACK_HOME:-$HOME/.gstack}"
LEARN_FILE="$GSTACK_HOME/projects/$SLUG/learnings.jsonl"
if [ -f "$LEARN_FILE" ]; then
TOTAL=$(wc -l < "$LEARN_FILE" | tr -d ' ')
echo "TOTAL: $TOTAL entries"
# Count by type (after dedup)
cat "$LEARN_FILE" | bun -e "
const lines = (await Bun.stdin.text()).trim().split('\n').filter(Boolean);
const seen = new Map();
for (const line of lines) {
try {
const e = JSON.parse(line);
const dk = (e.key||'') + '|' + (e.type||'');
const existing = seen.get(dk);
if (!existing || new Date(e.ts) > new Date(existing.ts)) seen.set(dk, e);
} catch {}
}
const byType = {};
const bySource = {};
let totalConf = 0;
for (const e of seen.values()) {
byType[e.type] = (byType[e.type]||0) + 1;
bySource[e.source] = (bySource[e.source]||0) + 1;
totalConf += e.confidence || 0;
}
console.log('UNIQUE: ' + seen.size + ' (after dedup)');
console.log('RAW_ENTRIES: ' + lines.length);
console.log('BY_TYPE: ' + JSON.stringify(byType));
console.log('BY_SOURCE: ' + JSON.stringify(bySource));
console.log('AVG_CONFIDENCE: ' + (totalConf / seen.size).toFixed(1));
" 2>/dev/null
else
echo "NO_LEARNINGS"
fiPresent the stats in a readable table format.
Manual add
The user wants to manually add a learning. Use AskUserQuestion to gather:
- Type (pattern / pitfall / preference / architecture / tool)
- A short key (2-5 words, kebab-case)
- The insight (one sentence)
- Confidence (1-10)
- Related files (optional)
Then log it:
~/.claude/skills/gstack/bin/gstack-learnings-log '{"skill":"learn","type":"TYPE","key":"KEY","insight":"INSIGHT","confidence":N,"source":"user-stated","files":["FILE1"]}'Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

